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Interactive Outlier Exploration in Big Data Streams

Summary: VSOutlier enables interactive exploration of outliers in big data streams with diverse types and efficient detection. Real-time analytics on stock transactions and moving-object streams help analysts identify, understand, and respond to phenomena. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11023
Venue
VLDB
Year
2014
Pagerank
7.8324917e-05
Overall Rank
3,031 | 79.21%
DOI
10.14778/2733004.2733058

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{cao_vldb14,
        title = {{Interactive Outlier Exploration in Big Data Streams}},
        author = {Cao, Lei and Wang, Qingyang and Rundensteiner, Elke A.},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {13},
        pages = {1621--1624},
        doi = {10.14778/2733004.2733058},
        url = {https://doi.org/10.14778/2733004.2733058},
        year = {2014}
}

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